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AI, data, automation: chemistry’s latest super-heroes!

Imagine your superpower was to know everything about chemistry AND be able to apply it to your scientific project! With AI, connected data and automation on our side, we are ready to accelerate innovation and solve the challenges of the future!

As you begin your science career, digitalization will play a big role in how you work. The arrival of Artificial intelligence (AI), connected data, and automation is set to revolutionize the way we approach scientific research.

One of the most remarkable transformations is the integration of AI in chemistry. By harnessing the power of AI, chemists are crafting eco-friendly solutions: that means reducing waste and developing sustainable alternatives to conventional methods.

Less than 35 years ago, Elias Corey won the Nobel Prize for Chemistry for his method of Retrosynthesis. Imagine what researchers will be able to do now that AI has access to two centuries of chemistry, all memorized by computers – AI models are increasingly indistinguishable from human experts in retrosynthesis tasks.

But that’s just the start… we know, for example, that if you provide AI with all Rembrandt’s paintings, the technology can conjure up new ‘Rembrandt’ paintings for us. If supplied with all the essential information of existing drugs and agrochemicals, will AI be able to conjure novel drugs? What does this mean for human society?

Big data is also making a big difference. Through extensive data collection and analysis, scientists are gaining valuable insights into complex chemical systems: this wealth of information helps identify patterns, trends, and correlations that were previously beyond our grasp, making it easier to develop greener and more efficient chemical strategies.

Furthermore, automation means we can streamline our work in the laboratory, as well as minimizing human error. By automating repetitive tasks, chemists can focus their energy on complex problem-solving and creative thinking. Even more than that, automation enables the creation of large amounts of high-quality data that can be used to make AI models even better.

With AI, big data and automation on our side, scientists can tackle even more intricate challenges.

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